Characteristics of Older Adults Who Meet the Annual Prescription Drug Expenditure Threshold for Medicare Medication Therapy Management Programs

BACKGROUND: The Medicare Modernization Act of 2003 requires drug plan sponsors to provide medication therapy management programs (MTMPs) to beneficiaries with (1) drug expenditures above $4,000, (2) multiple comorbidities, and (3) multiple prescription drugs. The Medical Expenditure Panel Survey (MEPS) is a national probability survey conducted annually by the Agency for Healthcare Research and Quality and the National Center for Health Statistics to provide nationally representative estimates of health care use, expenditures, sources of payments, and insurance coverage for the U.S. civilian noninstitutionalized population. MEPS comprises 3 components, including the household component (HC) in which households and individuals within households are sampled. The medical provider component (MPC) supplements the HC by contacting providers (hospitals, outpatient offices, home health agencies, and pharmacies) reported in the HC, and the insurance component collects data on health insurance plans and is separate from the HC. OBJECTIVES: The purpose of this study was to estimate from MEPS data for 2002-2003 (1) the proportion of older adults who may have met the $4,000 expenditure component of the MTMP criteria and (2) the patient-specific risk factors associated with meeting the $4,000 expenditure threshold. METHODS: This study is a cross-sectional analysis of MEPS respondents aged 65 years or older. Data came from both the MEPS-HC and the supplemental MEPS-MPC for 2002 and 2003. Specific data files were pooled and included the Full Year Consolidated files, Prescribed Medicines files, and the Medical Conditions files for both the 2002 and the 2003 MEPS-HC. Variables extracted from the MEPS data files included demographics, socioeconomic status, functional limitations, health status, presence and number of chronic conditions, body mass index, medical and prescription drug insurance, and health care utilization measures. The expenditure threshold of $4,000 was adjusted to $3,810 in 2003 U.S. dollars. Survey-weighted logistic regression identified factors associated with meeting the expenditure threshold. Unbiased population point estimates were obtained by adjusting for survey nonresponse, poststratification, and oversampling of blacks and Hispanics using MEPS person-level weights. In all analyses, standard errors were adjusted for nonindependence of observations due to complex multistage sampling by specifying the strata and primary sampling units for each respondent. RESULTS: Based on a sample of 8,035 noninstitutionalized persons aged 65 years or older in the United States, representing a population of 36.5 million older adults, MEPS data estimate that approximately 3.3 million (9.2%) incurred annual drug expenditures greater than $3,810, accounting for 35% of $55.3 billion in drug expenditures among all older adults. Older adults meeting the $3,810 prescription expenditure threshold reported an average 10.8 (SE=0.2) unique medications, 82.2 (SE=1.8) prescriptions, and 5.2 (SE=0.1) chronic conditions. Prescription expenditures accounted for 33.9% of total health care expenditures compared with 15.8% for persons who did not meet the $3,810 criterion and an average 19.5% for all persons aged 65 years or older (n=8,035). Factors that predicted meeting the expenditure threshold included age in 10-year increments (odds ratio [OR]=0.81; 95% confidence interval [CI], 0.68-0.97), requiring help with activities of daily living (OR=1.53; 95% CI, 1.19-1.97), having functional limitations (OR=1.67; 95% CI, 1.30-2.14), having TRICARE (military health care services) benefits (OR=0.54; 95% CI, 0.33-0.86), and being on Medicaid (OR=1.36; 95% CI, 1.02-1.81). Other factors that were also predictive of meeting the expenditure threshold included mental health disorders, ulcers, diabetes, dyslipidemia, cardiac disease, chronic obstructive pulmonary disorder, and the number of chronic conditions.

The statutory language of MMA defines MTMP eligibility broadly, giving PDP sponsors flexibility in defining the "targeted beneficiaries." While all Part D beneficiaries may benefit from the services that MTMPs provide, resource allocation is essential and PDP sponsors are being challenged with the task of determining eligibility within the legislation framework. 3 PDP sponsors face important issues when deciding how many diseases and prescription drugs will be used to identify candidates, if particular diseases and therapeutic areas will be targeted, or if a combination will be used. A comprehensive list of chronic diseases of interest is not specified in the MMA; however, diabetes, asthma, hypertension, hyperlipidemia, and congestive heart failure are mentioned as examples of conditions that may be targeted. 4 Finally, the high drug cost threshold introduces different considerations. For example, must a beneficiary incur an average of at least $333 per month in the first few months of the year to qualify for an MTMP based on the greater than $4,000 threshold criterion? In this case, beneficiaries would already be at a very high drug spending level, with a high likelihood of having already experienced adverse drug events or drug misuse, before receiving MTMP services. It has been suggested that the MMA criteria for MTMP candidates might be too limited and that it might be more cost effective for MTMP services to be used to prevent high-severity cases. 5 Our primary objectives were to obtain nationally representative estimates of the proportion of adults aged 65 years or older who would likely meet the high drug expenditure threshold and to identify characteristics that might help identify these candidates. We further intended to explore the significance of the $4,000 threshold as it relates to the other 2 criteria (have multiple chronic conditions and take multiple prescription medications) as well as prescription drug and overall health care use. To our knowledge, no studies have examined the explicit criteria of the MTMPs under the MMA legislation in such detail. year to year are not completely independent since households are drawn from the same geographic areas and persons may be in the sample for 2 consecutive years. Valid population estimates can, however, be determined when combining multiple MEPS years since each year of the MEPS-HC is designed to be nationally representative. 6 MEPS is a national probability survey cosponsored by the Agency for Healthcare Research and Quality (AHRQ) and the National Center for Health Statistics. MEPS is designed to provide nationally representative estimates of health care use, expenditures, source of payments, and insurance coverage for the U.S. civilian noninstitutionalized population. 7 Three components constitute each year of MEPS. The first component, the HC, represents the core survey in which households and individuals within households are sampled. Detailed, selfreported data are collected on demographic characteristics, health conditions, health status, income, health insurance coverage, employment, and both use and expenditures for health care services using computer-assisted personal interviewing technology. The HC uses an overlapping panel design in which data are collected over a series of 5 rounds (interviews) over a 2 1 /2-year period for each panel. Data collected, however, cover a complete 2-year period. A new panel is sampled and launched each year. Annual data are then generated by combining the last 3 rounds (3, 4, and 5) of the previous panel and the first 3 rounds (rounds 1, 2, and 3) of the new panel. Since MEPS began in 1996 with panel 1, this study has used data from rounds 3, 4, and 5 of panel 6 and rounds 1, 2, and 3 of panel 7 (2002 MEPS) combined with data from rounds 3, 4, and 5 of panel 7 and rounds 1, 2, and 3 of panel 8 (2003 MEPS).
The second component is the medical provider component (MPC), which supplements and/or replaces information on medical care expenditures reported by the HC by contacting all pharmacies and home health care agencies as well as a subsample of physicians and hospitals reported by the household respondents. The MPC is conducted through telephone interviews and record abstraction. The third component of MEPS is the insurance component (IC), which collects data on health insurance plans and is separate from the HC. Data collected from the MEPS-IC were not used in this study.
Data from the MEPS-HC and the supplemental information from the MEPS-MPC are available for public use in several downloadable data files. 8 The Full Year Consolidated Files for each year are person-level files and contain summary data for each respondent obtained from the MEPS-HC. Any expenditure data obtained from the MEPS-MPC are generally used in place of HC-reported expenditure data. When MPC data are not available, self-reported data from the HC are used. If neither source is available, expenditures are imputed from MPC data obtained for respondents with similar characteristics. The Medical Conditions files for each year are event-level data files that provide detailed information on each medical condition reported by the household respondent. All data in this file are self-reported data.
The Prescribed Medicines files are also event-level files that contain data on all prescribed medicines, including refills, reported by the respondent of the HC, and are supplemented with detailed data (total amount charged by the pharmacy, all payments by source including third-party and out-of-pocket, National Drug Code, strength, and quantity dispensed) from MPC pharmacies. 9,10 Data were obtained from MPC pharmacies through telephone interview and computerized printouts from pharmacies if the HC respondent provided written permission to release such data. Imputation methods were used in cases where pharmacy data were not available. 11

Medication Therapy Management Expenditure Threshold
All expenditure data were adjusted to constant 2003 U.S. dollars using the consumer price index for all items averaged across all U.S. cities. 12 The 2003 U.S. dollar equivalent of $4,000 was determined to be $3,810 in 2006. The main study comparison groups were older adults with annual prescription drug expenditures (from all payment sources) greater than $3,810 and those with prescription expenditures equal to or below this level.

Identification of Risk Factors
We hypothesized that patient characteristics known to relate to medical and prescription drug expenditures would be key risk factors for being in the high-expenditure group. These factors included demographic and socioeconomic characteristics; medical and prescription drug insurance; perceived health and mental health status; requiring assistance with activities of daily living (ADLs); functional, cognitive, or sensory limitations; body mass index (BMI); and both the presence and count of chronic diseases.
Demographic characteristics included age (continuous variable with results reported for 10-year increments), gender, race/ ethnicity, and marital status. Socioeconomic factors included education and total annual personal income (2003 U.S. dollars). As described above, each panel contributes 3 rounds of data to each MEPS year (for example, in 2002, panel 6 contributed rounds 3, 4, and 5, while panel 7 contributed rounds 1, 2, and 3), resulting in round-specific variables. Also, because of the overlapping panel design, each round in one panel occurs at the same time as each round in the next panel (for example in 2002, round 3 of panel 6 occurred at the same time as round 1 of panel 7). Consequently, data from overlapping rounds were combined across panels. Unless otherwise noted, annual summary variables were used that reflect respondent status as of December 31 of the corresponding year (as in age and marital status). For each year, 3 round-specific health status variables and 3 round-specific mental health status variables (coded as "excellent," "very good," "good," "fair," and "poor") were available. Since these variables could not be pooled into an annual variable, the mode of the round-specific variables was used to create an overall health status variable and an overall mental health status variable. In cases with multiple modes (either due to nonresponse in one of the rounds or a different response in each of the 3 round-specific variables), the response reflecting poorer health status was used. The "excellent" and "very good" responses were combined for both health status variables to increase reliability of the population estimates.
A total of 5 functional limitation variables were extracted, each a binary (yes/no) variable. If a "yes" was reported during any of the 3 rounds, the respondent was included in this analysis as having the corresponding limitation. These variables included (1) requiring assistance with ADLs, e.g., bathing, dressing), (2) requiring assistance with instrumental ADLs (IADLs, e.g., paying bills, doing laundry), (3) having any reported difficulties with walking, lifting, bending, or limitations with housework, (4) having cognitive difficulties, and (5) reporting any vision or hearing problems throughout the year.
Four medical insurance variables were created from selfreported data: Medicare, Medicaid, private health insurance, and TRICARE (military health care services). Each variable was considered present if the respondent indicated having the corresponding insurance during any round. The presence of prescription drug insurance was determined using self-report and sources of payment in the Prescribed Medicines file. If a respondent indicated having private drug insurance during any round or if any third-party payment was recorded in the Prescribed Medicines file, the respondent was considered to have prescription drug insurance at some point during the year. This method has been used in previous studies. [13][14][15] MEPS professional coders assign International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to each medical condition reported by the household respondent. These codes for conditions as well as ICD-9 procedure codes were aggregated into 260 mutually exclusive, clinically meaningful categories using Clinical Classification software. 16 From these categories, 25 major chronic conditions were identified based on importance and relevance in the older adult population. Medical service use variables included annual counts of office-based visits, outpatient visits, inpatient discharges and nights, emergency department visits, and home health care visits. Annual total medical expenditures and nonpharmacy medical expenditures were also extracted. Annual totals of prescription drug acquisitions and prescription drug expenditures as well as sources of payment were collected from the MEPS HC. Therapeutic class was determined from Multum Lexicon classifications 17 for all drugs reported by the respondent and was provided by MEPS in the Prescribed Medicines files. 9,10 Statistical Analysis Nationally representative estimates were obtained using respondents with a person-level weight, which accounts for survey nonresponse, poststratification, and oversampling of blacks and Hispanics. To preserve the survey design structure and yield valid standard errors, we used the full person-level files when calculating estimates of subpopulations. Standard errors were adjusted for complex survey design with the use of a Taylor-series linearization approach while specifying strata and primary sampling units from which each respondent was sampled. Bivariate comparisons between the 2 prescription Characteristics of Older Adults Who Meet the Annual Prescription Drug Expenditure Threshold for Medicare Medication Therapy Management Programs drug cost groups on categorical and continuous variables were made with survey-weighted chi-squared tests and t tests, respectively. Survey-weighted logistic regression examined the association of study population characteristics with high annual drug expenditures.

Study Population Characteristics by Amount of Prescription Drug Expenditure
All candidate risk factors, except for chronic diseases with less than 5% reported prevalence in the high-cost group, were initially included in the model. To arrive at a parsimonious model, a backward elimination process eliminated nonsignificant variables at the α = 0.05 level. Variables forced in the model regardless of statistical significance included age, gender, education, race, income, and prescription drug insurance. All statistical analyses were conducted using Stata version 8.2 (StataCorp, College Station, Texas).
ss Results Table 1 displays the sample size of the surveyed sample, the corresponding population size to which MEPS estimates can be extrapolated, and comparisons on population characteristics. A total of 8,035 MEPS respondents represented nearly 36.5 million U.S. civilian noninstitutionalized adults aged 65 years and older. Approximately 3.3 million of these older adults (9.2%) qualified for MTMP using the $3,810 expenditure threshold. The group of older adults who met the expenditure threshold had a higher percentage of females (P <0.001) and widowers (P = 0.021) and reported fewer years of education (P <0.001) compared with the group of older adults below the expenditure threshold. Furthermore, reported income for the high-cost group was significantly lower than the group not meeting the expenditure threshold ($18,733 vs. $23,221, P <0.001).
More than half (52.7 %) of older adults meeting the expenditure threshold reported having fair or poor overall health and tended to also report significantly poorer overall health and mental health than did those not meeting the criterion (P <0.001). Also, those with high prescription expenditures more frequently reported requiring help with ADLs and IADLs as well as having functional, cognitive, and sensory limitations (all P values <0.001). Those with high prescription expenditures also had a higher BMI (28.3 vs. 24.5, P <0.001), with the average being in the overweight category, than did those not meeting the expenditure threshold.
Older adults meeting the expenditure threshold had a higher percentage of respondents reporting Medicaid benefits (P <0.001) or Medicare benefits (P=0.035) at some point over the year and a lower percentage of older adults having TRICARE (P = 0.016) compared with those not meeting the expenditure threshold. Furthermore, 80% of those meeting the criterion were estimated to have prescription drug insurance at any time over the year, compared with 68% of those not meeting the expenditure threshold (P <0.001).
Estimates of chronic disease prevalence between the 2 groups are displayed in Table 2. Hypertension, osteoarthritis/joint disorders, cardiac disease, and dyslipidemia were the most prevalent conditions reported overall. Hypertension and cardiac disease were reported in more than half of the study population in the high-cost group. Other notable differences were a higher prevalence of diabetes, mental disorders, ulcers, and asthma. Older adults who met the criterion reported an average of 5.2 (±SE = 0.11) chronic conditions (2.3 more conditions than those in the lower-cost group, P <0.001). As illustrated in Figure 1A, more than 60% of older adults meeting the expenditure threshold reported 5 or more chronic conditions, while the majority of those not meeting the criterion reported between 1 and 3 chronic conditions.
Significant predictors of expenditure group membership were evaluated using logistic regression and are shown in Table 3 Furthermore, older adults with 6 or more chronic diseases were 6 times more likely to be in the high-cost group than those with fewer than 3 chronic diseases (OR = 6.14; 95% CI, 3.86-9.78). Table 4 summarizes prescription drug use and overall health care use within the study population. Older adults meeting the expenditure threshold represented 9.2% of the population and accounted for 35.4% of the $55 billion in annual prescription drug expenditures, used significantly more prescriptions annually (82.2 ± 1.76), and obtained more unique medications (10.8 ± 0.2) compared with those not meeting the expenditure threshold (20.3 ± 0.37 prescriptions and 4.6 ± 0.06 unique medications). In addition, the average prescription cost was $28 higher for older adults who met the expenditure threshold than for those not meeting the threshold. Older adults meeting the expenditure threshold incurred approximately $10,000 higher total health care expenditures ($17,271 vs. $6,840, P <0.001) and $5,600 higher nonpharmacy medical expenditures ($11,416 vs. $5,761, P <0.001) than did those not meeting the expenditure threshold. Furthermore, 33.9% of total health care expenditures for older adults meeting the expenditure threshold went to prescription drugs, while 15.8% of total health care expenditures went to prescription drugs for persons who did not meet the Characteristics of Older Adults Who Meet the Annual Prescription Drug Expenditure Threshold for Medicare Medication Therapy Management Programs $3,810 criterion. Those in the high-cost group also incurred higher levels of health care services, including office-based and hospital-based office visits, emergency department visits, inpatient admissions, and home health care visits. Figure 1B illustrates the distribution of the number of unique medications obtained by the study population. All older adults meeting the expenditure threshold obtained at least 3 unique medications; approximately 68% obtained 9 or more unique medications.
The proportion of total annual drug expenditures accounted for by therapeutic drug classes is displayed in Table 5. Cardiovascular drugs consumed the largest portion for both expenditure groups and was significantly lower for older adults meeting the expenditure threshold than for those not meeting the threshold (20.1% vs. 28.6, P <0.05). No significant differences were observed between the expenditure groups with respect to the use of hormones as a group; however, antidiabetic drugs accounted for a larger percentage of total drug expenditures among older adults meeting the expenditure threshold compared with those not meeting the threshold (9.3 vs. 6.1%, P <0.001).

Characteristics of Older Adults Who Meet the Annual Prescription Drug Expenditure Threshold for Medicare Medication Therapy Management Programs
Other drug classes that accounted for a significantly higher proportion of the total drug expenditures among older adults meeting the criterion included proton pump inhibitors, psychotherapeutic agents, respiratory agents, and coagulation modifiers. The estimates of the number of chronic diseases and annual prescription drug costs are generally consistent with those reported from other sources. Data from the 2002 Medicare Current Beneficiary Survey estimated that approximately 90% of Medicare beneficiaries had at least 1 chronic condition. 18 We estimated that 91% of older adults had at least 1 chronic condition. Reports from the Congressional Budget Office (CBO) and the AARP Public Policy Institute estimate that average per capita drug expenditure for Medicare beneficiaries in 2003 was $2,318 19 and that Medicare beneficiaries aged 65 years or older averaged $830 in out-of-pocket spending for prescription drugs in 2003. 20 This study' s estimate for average per capita drug expenditures, $1,517, was lower than that of the CBO; however, this difference may be partially explained by the target population being noninstitutionalized older adults rather than all Medicare beneficiaries. This study also estimated that approximately 54% of annual drug expenditures were paid out of pocket, about $819 on average.
Approximately 97% of the older adults who incurred annual drug expenditures in excess of the MTMP threshold had 2 or more chronic diseases; all had at least 3 unique medications filled during the year. This finding indicates a redundancy in the criteria and suggests that focusing on the high drug expenditure threshold may be an effective approach for identifying MTMP candidates, while still keeping with the 3 general provisions.
Although unadjusted differences in age were not different between older adults meeting the expenditure threshold and those not meeting the expenditure threshold, age was negatively correlated and significant in the regression model when it was adjusted for all other covariates entered. This result may suggest that, after adjusting for important characteristics such as demographics and comorbidity burden, we found that those adults between 65 and 75 years may be more aggressively treated for their conditions and may have higher medical use than those who are older. We did not explore this possibility. Older adults who reported requiring help with ADLs were 53% more likely to meet the expenditure threshold, and those reporting functional limitations were 67% more likely to have annual prescription drug expenditures in excess of $3,810, compared

Characteristics of Older Adults Who Meet the Annual Prescription Drug Expenditure Threshold for Medicare Medication Therapy Management Programs
with those not reporting either limitation. Unfortunately, selfreported data on ADLs and other functional limitations will not be available from pharmacy claims, making the role of physicians and nurse practitioners significant in identifying MTMP candidates. Chronic diseases that increased the likelihood of having high prescription drug expenditures included mental disorders, stomach/duodenal ulcers, diabetes, dyslipidemia, cardiac disease, and COPD. Drug plans may target beneficiaries with these diseases in conjunction with a raw count, using medical and/or pharmacy claims, in complying with the "multiple chronic diseases" criteria. Compared with older adults with fewer than 2 reported chronic diseases, those with 6 or more diseases were 6 times as likely to have high prescription drug expenditures.
Results from testing medical and prescription drug insurance were noteworthy. Respondents with Medicaid coverage at some point over the year were 36% more likely and those with TRI-CARE were 54% less likely to meet the expenditure threshold. Independent of medical insurance, having any prescription drug insurance was not a significant predictor of group membership. Furthermore, older adults meeting the expenditure threshold not only used more classes of prescription drugs, but they also obtained more total fills (including refills) and obtained medications that were, on average, $28 per prescription more expensive than older adults in the lower cost group. The results have substantial implications for PDP sponsors and for Medicare that underscore the importance of effective MTMP. For one, there is a high level of comorbidity burden and prescription drug use among older adults who met the expenditure threshold. The negative consequences of polypharmacy

Characteristics of Older Adults Who Meet the Annual Prescription Drug Expenditure Threshold for Medicare Medication Therapy Management Programs
and inappropriate prescribing among older adults have been well cited. 21-37 The prevalence of inappropriate drug use among ambulatory older adults is estimated between 17% and 48%. [23][24][25][26][27][28][29] Inappropriate drug use is associated with adverse drug reactions (ADRs), drug-related hospital admissions, increased outpatient visits, and decline in functional status among the elderly. 23,25,27,28,30 Polypharmacy among older adults increases the incidence of inappropriate drug use, 31,32 ADRs, [33][34][35] and drug-drug interactions. The number of potential interactions increases in a logarithmic fashion as the number of medications increases. 38 Seniors represent the greatest proportion of the population at risk for exposure to a potential clinically significant interaction. 39 Prescription Drug and Health Care Utilization by Expenditure Threshold*

Characteristics of Older Adults Who Meet the Annual Prescription Drug Expenditure Threshold for Medicare Medication Therapy Management Programs
The incidence of adverse drug events (ADEs) resulting from either medication errors or ADRs is estimated at 27% per year among older adults in the ambulatory setting. 40 Approximately 39% of these ADEs were considered ameliorable or preventable and were attributed to poor communication between physician and patient regarding ADE symptoms and prescribing errors, respectively. 40 Both the level of comorbidity burden and the number of medications used have demonstrated dose-response relationships with the risk of ADEs. 41 Furthermore, ADEs among older adults in the ambulatory setting have been associated with $1,310 and $1,983 higher medical costs, respectively, in the 6 weeks post-ADE onset compared with the 6 weeks pre-ADE. 42 Pharmacists, along with physicians and nurse practitioners, are in unique positions to identify potential candidates for MTMP services. However, identifying potential candidates is only the first step because providers of these services will face substantial challenges. Older adults experience high rates of inappropriate drug use, polypharmacy, and ADEs, and as a more medically complex group, MTMP candidates will represent a special population in which such services can have a significant impact. Community pharmacists may be a logical choice as providers of MTMP services because of their accessibility to beneficiaries and their in-depth training and experience in providing pharmaceutical care. 43 Pharmacists, either as leaders of interventions or as members of a disease management team, have contributed to improvements in outcomes and compliance in patients with hypertension and heart failure. [44][45][46][47][48] Community pharmacist-led services can improve patient outcomes and change patient behavior across chronic conditions, including hypertension, hypercholesterolemia, heart failure, and diabetes. 49 Clinical pharmacy services in ambulatory older adults have led to improvements in the quality of drug use, patient adherence, and suboptimal prescribing. 50 In a study of patients from Veterans Affairs medical centers at high risk for drug-related problems, pharmacist interventions resolved 69% of medication-related problems, significantly improved lipid measurements in patients with dyslipidemia, and demonstrated a dose-response relationship between quality of life and the number of pharmacist contacts. 51,52 Also, despite the increased number of clinic visits and costs of pharmacist interventions, overall health care expenditures were similar for patients randomized to see a clinical pharmacist versus usual medical care. 53 Despite the observed benefits of pharmacist-led interventions, evidence of the extent of their effectiveness has been inconsistent due to small sample sizes, lack of appropriate adjustment for confounding, and variation in the interventions and definitions of pharmaceutical care. 45,54 Another implication for Medicare is that older adults who met the prescription expenditure threshold incurred significantly higher total health care and nonpharmacy medical expenditures. This group was also more likely to have outpatient visits, inpatient and emergency department admissions, and home health visits. Medicare spending exceeded $300 billion in 2004, with the costliest 5% [of beneficiaries] accounting for 43% of total spending. In light of these estimates and the rapid growth in Medicare spending, a push to focus on high-cost Medicare beneficiaries has been advocated. 55 From the perspective of Medicare, these findings highlight that the importance of focusing on beneficiaries who qualify for MTMP services stretches far beyond prescription drug use.

Limitations
First, our results should be interpreted in the context that this study relies heavily on self-reported data and has potential for errors in data collection, editing, and imputation. For example, the data used to determine the number of chronic conditions came from the 2002 and 2003 Medical Conditions files and were based on an assigned ICD-9-CM code imputed by MEPS professional coders for each condition reported. The extent that these conditions were truly chronic within the study population was not verified and may have overestimated the level of comorbidity within the study population. Second, although our estimates for the older adult population are consistent with other studies, only 53% of the prescribed medicines from the MPC pharmacies were exactly matched to drug mentions in the HC. Exact matches were based on drug code, medication name, and the round in which the drug was reported. Drug mentions in the HC that were not exactly matched to MPC pharmacy data were statistically matched to the entire MPC pharmacy data by medication name, drug code, type of third-party coverage, health conditions, age, sex, and other characteristics of the individual to obtain expenditure information. 11 Third, because of the significant editing, coding, and accuracy checks that MEPS data incur before being released, there is a 3-year lag between the year released and the data year. Recently, data from 2004 became available from MEPS. Fourth, older adults who chose to have prescription drug insurance might have been more likely to be in the high-expenditure group (either from adverse selection, moral hazard, or a combination of the two). We were unable to measure the extent of these 2 phenomena; however, after controlling for other significant predictors, having any type of insurance coverage for prescription drugs was not significant as a predictor of meeting the expenditure threshold. Older adults who would have qualified had substantially more chronic conditions, were more likely to report requiring help with ADLs, were more likely to report having functional difficulties such as walking, lifting, and performing housework, and were more likely to be on Medicaid.